On Misalignment Between Magnetometer and Inertial Sensors

Magnetometer, gyroscope, and accelerometer are commonly used sensors in a variety of applications. In addition to sensor's physical imperfection, magnetometer's parameters are also affected by magnetic disturbance. Specifically, the soft-iron magnetic effect not only changes its intrinsic model parameters, including the scale factor, orthogonality matrix, and bias, but also its relative misalignment with respect to other sensors, such as inertial sensors of interest in this paper. Almost all existing methods rely on the local gravity information for cross-sensor calibration, thus requiring to collect accelerometer measurements at static positions. Based on the rationale that in a homogenous magnetic field the magnetometer's measurement variation is exclusively induced by orientation change, this paper proposes a novel magnetometer-inertial sensor misalignment estimation algorithm requiring no local gravity information. Founded on a constrained optimization, the algorithm is recursive in time with self-initialization and is also capable of estimating the gyroscope bias as an added benefit. Field test results show that the proposed algorithm has quite good estimation accuracy. As it is inherently immune to any acceleration disturbance, the test equipment does not have to keep still for effective measurement.